from sklearn_benchmarks.report import Reporting, ReportingHpo, print_time_report, print_env_info
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
scikit-learn vs. scikit-learn-intelex (Intel® oneAPI) benchmarks: perfect hyperparameters match¶print_time_report()
sklearnex_KMeans_short: 0h 0m 1s
sklearnex_Ridge: 0h 0m 2s
KMeans_short: 0h 0m 2s
sklearnex_LogisticRegression: 0h 0m 4s
sklearnex_KMeans_tall: 0h 0m 7s
Ridge: 0h 0m 11s
LogisticRegression: 0h 0m 20s
KMeans_tall: 0h 0m 22s
sklearnex_KNeighborsClassifier_kd_tree: 0h 0m 28s
sklearnex_KNeighborsClassifier: 0h 2m 26s
KNeighborsClassifier_kd_tree: 0h 2m 38s
catboost_lossguide: 0h 5m 3s
xgboost: 0h 5m 8s
lightgbm: 0h 5m 11s
catboost_symmetric: 0h 5m 19s
HistGradientBoostingClassifier: 0h 5m 32s
KNeighborsClassifier: 0h 34m 5s
total: 1h 7m 7s
print_env_info()
{
"system_info": {
"python": "3.8.10 | packaged by conda-forge | (default, May 11 2021, 07:01:05) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.8.0-1036-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1.3",
"setuptools": "49.6.0.post20210108",
"sklearn": "1.0.dev0",
"numpy": "1.21.0",
"scipy": "1.7.0",
"Cython": null,
"pandas": "1.3.0",
"matplotlib": "3.4.2",
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.15.so",
"prefix": "libopenblas",
"user_api": "blas",
"internal_api": "openblas",
"version": "0.3.15",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/python3.8/site-packages/scikit_learn.libs/libgomp-f7e03b3e.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}
reporting = Reporting(config="config.yml")
reporting.run()
KNeighborsClassifier: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.132 | 0.0 | 6.066 | 0.0 | -1 | 100 | NaN | NaN | 0.482 | 0.0 | 0.274 | 0.0 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.127 | 0.0 | 6.291 | 0.0 | -1 | 5 | NaN | NaN | 0.468 | 0.0 | 0.272 | 0.0 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.128 | 0.0 | 6.245 | 0.0 | 1 | 1 | NaN | NaN | 0.468 | 0.0 | 0.274 | 0.0 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.128 | 0.0 | 6.258 | 0.0 | 1 | 100 | NaN | NaN | 0.458 | 0.0 | 0.279 | 0.0 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.123 | 0.0 | 6.485 | 0.0 | -1 | 1 | NaN | NaN | 0.458 | 0.0 | 0.269 | 0.0 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.122 | 0.0 | 6.568 | 0.0 | 1 | 5 | NaN | NaN | 0.458 | 0.0 | 0.266 | 0.0 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.054 | 0.0 | 0.299 | 0.0 | -1 | 100 | NaN | NaN | 0.096 | 0.0 | 0.557 | 0.0 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.064 | 0.0 | 0.250 | 0.0 | -1 | 5 | NaN | NaN | 0.096 | 0.0 | 0.668 | 0.0 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.054 | 0.0 | 0.299 | 0.0 | 1 | 1 | NaN | NaN | 0.103 | 0.0 | 0.520 | 0.0 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.053 | 0.0 | 0.300 | 0.0 | 1 | 100 | NaN | NaN | 0.096 | 0.0 | 0.553 | 0.0 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.053 | 0.0 | 0.302 | 0.0 | -1 | 1 | NaN | NaN | 0.096 | 0.0 | 0.550 | 0.0 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.053 | 0.0 | 0.300 | 0.0 | 1 | 5 | NaN | NaN | 0.097 | 0.0 | 0.552 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 35.370 | 0.000 | 0.0 | 0.035 | -1 | 100 | 0.942 | 0.932 | 1.778 | 0.005 | 19.894 | 0.060 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.186 | 0.017 | 0.0 | 0.186 | -1 | 100 | 1.000 | 1.000 | 0.086 | 0.000 | 2.171 | 0.201 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 34.789 | 0.000 | 0.0 | 0.035 | -1 | 5 | 0.806 | 0.932 | 1.780 | 0.006 | 19.540 | 0.067 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.186 | 0.011 | 0.0 | 0.186 | -1 | 5 | 1.000 | 1.000 | 0.088 | 0.006 | 2.106 | 0.185 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 12.670 | 0.026 | 0.0 | 0.013 | 1 | 1 | 0.702 | 0.828 | 1.788 | 0.144 | 7.087 | 0.572 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.195 | 0.001 | 0.0 | 0.195 | 1 | 1 | 1.000 | 1.000 | 0.085 | 0.000 | 2.283 | 0.018 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 21.539 | 0.082 | 0.0 | 0.022 | 1 | 100 | 0.942 | 0.691 | 1.734 | 0.004 | 12.422 | 0.055 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.205 | 0.001 | 0.0 | 0.205 | 1 | 100 | 1.000 | 1.000 | 0.087 | 0.000 | 2.362 | 0.016 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 26.128 | 0.338 | 0.0 | 0.026 | -1 | 1 | 0.702 | 0.691 | 1.738 | 0.012 | 15.031 | 0.221 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.179 | 0.017 | 0.0 | 0.179 | -1 | 1 | 1.000 | 1.000 | 0.086 | 0.000 | 2.083 | 0.203 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 21.335 | 0.026 | 0.0 | 0.021 | 1 | 5 | 0.806 | 0.828 | 1.738 | 0.004 | 12.279 | 0.035 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.203 | 0.001 | 0.0 | 0.203 | 1 | 5 | 1.000 | 1.000 | 0.086 | 0.000 | 2.373 | 0.010 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 34.394 | 0.000 | 0.0 | 0.034 | -1 | 100 | 0.985 | 0.982 | 0.297 | 0.000 | 115.830 | 0.113 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.031 | 0.002 | 0.0 | 0.031 | -1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 6.016 | 0.628 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 34.443 | 0.000 | 0.0 | 0.034 | -1 | 5 | 0.980 | 0.982 | 0.298 | 0.002 | 115.694 | 0.756 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.031 | 0.003 | 0.0 | 0.031 | -1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 6.094 | 0.747 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 10.072 | 0.004 | 0.0 | 0.010 | 1 | 1 | 0.973 | 0.982 | 0.251 | 0.000 | 40.103 | 0.070 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.014 | 0.001 | 0.0 | 0.014 | 1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 2.753 | 0.251 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 21.017 | 0.019 | 0.0 | 0.021 | 1 | 100 | 0.985 | 0.974 | 0.250 | 0.001 | 83.915 | 0.254 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.022 | 0.001 | 0.0 | 0.022 | 1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 4.507 | 0.465 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 23.586 | 0.151 | 0.0 | 0.024 | -1 | 1 | 0.973 | 0.974 | 0.250 | 0.000 | 94.440 | 0.625 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.020 | 0.002 | 0.0 | 0.020 | -1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 3.977 | 0.506 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 20.905 | 0.053 | 0.0 | 0.021 | 1 | 5 | 0.980 | 0.982 | 0.251 | 0.001 | 83.222 | 0.282 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.023 | 0.000 | 0.0 | 0.023 | 1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 4.566 | 0.398 | See | See |
KNeighborsClassifier_kd_tree: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.719 | 0.0 | 0.029 | 0.0 | 1 | 1 | NaN | NaN | 0.711 | 0.0 | 3.821 | 0.0 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.718 | 0.0 | 0.029 | 0.0 | -1 | 5 | NaN | NaN | 0.713 | 0.0 | 3.813 | 0.0 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.719 | 0.0 | 0.029 | 0.0 | -1 | 100 | NaN | NaN | 0.706 | 0.0 | 3.853 | 0.0 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.766 | 0.0 | 0.029 | 0.0 | -1 | 1 | NaN | NaN | 0.704 | 0.0 | 3.928 | 0.0 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.791 | 0.0 | 0.029 | 0.0 | 1 | 100 | NaN | NaN | 0.724 | 0.0 | 3.852 | 0.0 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.799 | 0.0 | 0.029 | 0.0 | 1 | 5 | NaN | NaN | 0.704 | 0.0 | 3.975 | 0.0 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.708 | 0.0 | 0.023 | 0.0 | 1 | 1 | NaN | NaN | 0.429 | 0.0 | 1.648 | 0.0 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.708 | 0.0 | 0.023 | 0.0 | -1 | 5 | NaN | NaN | 0.442 | 0.0 | 1.603 | 0.0 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.709 | 0.0 | 0.023 | 0.0 | -1 | 100 | NaN | NaN | 0.473 | 0.0 | 1.501 | 0.0 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.692 | 0.0 | 0.023 | 0.0 | -1 | 1 | NaN | NaN | 0.427 | 0.0 | 1.620 | 0.0 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.700 | 0.0 | 0.023 | 0.0 | 1 | 100 | NaN | NaN | 0.427 | 0.0 | 1.640 | 0.0 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.693 | 0.0 | 0.023 | 0.0 | 1 | 5 | NaN | NaN | 0.460 | 0.0 | 1.505 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.737 | 0.003 | 0.000 | 0.001 | 1 | 1 | 0.966 | 0.977 | 0.195 | 0.003 | 3.784 | 0.058 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 10.800 | 6.428 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.830 | 0.005 | 0.000 | 0.001 | -1 | 5 | 0.976 | 0.978 | 0.574 | 0.003 | 1.447 | 0.012 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.006 | 0.002 | 0.000 | 0.006 | -1 | 5 | 0.000 | 1.000 | 0.001 | 0.000 | 7.488 | 4.152 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.793 | 0.023 | 0.000 | 0.003 | -1 | 100 | 0.973 | 0.960 | 0.106 | 0.001 | 26.336 | 0.381 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.012 | 0.002 | 0.000 | 0.012 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 52.821 | 29.869 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.437 | 0.010 | 0.000 | 0.000 | -1 | 1 | 0.966 | 0.978 | 0.571 | 0.001 | 0.766 | 0.017 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.004 | 0.001 | 0.000 | 0.004 | -1 | 1 | 1.000 | 1.000 | 0.001 | 0.000 | 5.446 | 3.002 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 4.984 | 0.167 | 0.000 | 0.005 | 1 | 100 | 0.973 | 0.960 | 0.105 | 0.001 | 47.403 | 1.643 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.008 | 0.002 | 0.000 | 0.008 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 39.569 | 24.619 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 1.457 | 0.007 | 0.000 | 0.001 | 1 | 5 | 0.976 | 0.977 | 0.196 | 0.002 | 7.448 | 0.073 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 5 | 0.000 | 1.000 | 0.000 | 0.000 | 15.638 | 9.957 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.021 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.963 | 0.985 | 0.001 | 0.000 | 19.033 | 4.606 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 5.640 | 4.747 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.024 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.974 | 0.982 | 0.006 | 0.001 | 3.871 | 0.499 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 18.473 | 13.737 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.040 | 0.002 | 0.000 | 0.000 | -1 | 100 | 0.975 | 0.975 | 0.001 | 0.000 | 53.370 | 20.632 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 21.041 | 15.749 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.023 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.963 | 0.982 | 0.006 | 0.001 | 3.699 | 0.460 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 19.436 | 15.196 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.043 | 0.004 | 0.000 | 0.000 | 1 | 100 | 0.975 | 0.975 | 0.001 | 0.000 | 56.550 | 22.799 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 5.741 | 4.598 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.022 | 0.001 | 0.001 | 0.000 | 1 | 5 | 0.974 | 0.985 | 0.001 | 0.000 | 20.827 | 6.148 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 5.224 | 4.752 | See | See |
KMeans_tall: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.609 | 0.0 | 0.788 | 0.0 | k-means++ | NaN | 30 | NaN | 0.385 | 0.0 | 1.584 | 0.0 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.474 | 0.0 | 1.012 | 0.0 | random | NaN | 30 | NaN | 0.397 | 0.0 | 1.193 | 0.0 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 6.583 | 0.0 | 3.646 | 0.0 | k-means++ | NaN | 30 | NaN | 2.592 | 0.0 | 2.539 | 0.0 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 5.891 | 0.0 | 4.074 | 0.0 | random | NaN | 30 | NaN | 2.744 | 0.0 | 2.147 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.001 | 0.0 | 0.359 | 0.000 | k-means++ | 0.001 | 30 | 0.001 | 0.0 | 0.0 | 9.391 | 6.219 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.001 | 0.0 | 0.000 | 0.001 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 11.265 | 8.074 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.001 | 0.0 | 0.357 | 0.000 | random | 0.001 | 30 | 0.001 | 0.0 | 0.0 | 9.380 | 6.745 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.001 | 0.0 | 0.000 | 0.001 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.835 | 7.043 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 14.718 | 0.000 | k-means++ | 0.002 | 30 | 0.002 | 0.0 | 0.0 | 6.326 | 3.437 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.001 | 0.0 | 0.019 | 0.001 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.853 | 7.467 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 15.450 | 0.000 | random | 0.002 | 30 | 0.002 | 0.0 | 0.0 | 5.921 | 2.966 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.001 | 0.0 | 0.019 | 0.001 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.877 | 7.840 | See | See |
KMeans_short: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.207 | 0.0 | 0.015 | 0.0 | k-means++ | NaN | 20 | NaN | 0.027 | 0.0 | 7.693 | 0.0 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.071 | 0.0 | 0.045 | 0.0 | random | NaN | 20 | NaN | 0.080 | 0.0 | 0.890 | 0.0 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.550 | 0.0 | 0.291 | 0.0 | k-means++ | NaN | 20 | NaN | 0.112 | 0.0 | 4.904 | 0.0 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.186 | 0.0 | 0.861 | 0.0 | random | NaN | 20 | NaN | 0.286 | 0.0 | 0.650 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.0 | 0.185 | 0.000 | k-means++ | -0.002 | 20 | -0.000 | 0.000 | 0.0 | 3.465 | 0.765 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.001 | 0.0 | 0.000 | 0.001 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.328 | 7.989 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.0 | 0.187 | 0.000 | random | 0.001 | 20 | 0.001 | 0.000 | 0.0 | 3.447 | 0.708 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.001 | 0.0 | 0.000 | 0.001 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.766 | 7.474 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.0 | 6.743 | 0.000 | k-means++ | 0.341 | 20 | 0.297 | 0.001 | 0.0 | 2.360 | 0.441 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.001 | 0.0 | 0.012 | 0.001 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 9.133 | 5.286 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.0 | 6.685 | 0.000 | random | 0.370 | 20 | 0.337 | 0.001 | 0.0 | 2.425 | 0.409 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.001 | 0.0 | 0.012 | 0.001 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 9.018 | 5.028 | See | See |
LogisticRegression: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_informative | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 11.348 | 0.0 | [-0.10397258] | 0.000 | NaN | NaN | NaN | NaN | NaN | 1.930 | 0.0 | 5.880 | 0.0 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [27] | 0.810 | 0.0 | [-2.63517582] | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.913 | 0.0 | 0.887 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_informative | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 0.000 | 0.0 | [57.94972429] | 0.0 | NaN | NaN | NaN | NaN | 0.562 | 0.000 | 0.0 | 0.809 | 0.460 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 0.000 | 0.0 | [0.24686558] | 0.0 | NaN | NaN | NaN | NaN | 1.000 | 0.000 | 0.0 | 0.374 | 0.367 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [27] | 0.002 | 0.0 | [139.64539121] | 0.0 | NaN | NaN | NaN | NaN | 0.280 | 0.003 | 0.0 | 0.557 | 0.121 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [27] | 0.000 | 0.0 | [25.98221181] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.001 | 0.0 | 0.125 | 0.102 | See | See |
Ridge: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_informative | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.174 | 0.0 | 0.461 | 0.0 | NaN | NaN | NaN | 0.174 | 0.0 | 0.997 | 0.0 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 1.462 | 0.0 | 0.547 | 0.0 | NaN | NaN | NaN | 0.225 | 0.0 | 6.497 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_informative | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.011 | 0.0 | 7.098 | 0.0 | NaN | NaN | 0.11 | 0.018 | 0.0 | 0.624 | 0.017 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.000 | 0.0 | 1.151 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.649 | 0.717 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.000 | 0.0 | 5.748 | 0.0 | NaN | NaN | 1.00 | 0.000 | 0.0 | 0.621 | 0.510 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.000 | 0.0 | 0.014 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.647 | 0.746 | See | See |